Evidence map›Paper›PMID 39061773›Full record

ArticleBioengineering (Basel, Switzerland)2024

Intuitionistic Fuzzy Biofeedback Control of Implanted Dual-Sensor Cardiac Pacemakers.

Hussain Alshahrani, Amnah Alshahrani, Mohamed Esmail Karar, Ebrahim A Ramadan

Abstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Hussain AlshahraniDepartment of Computer Science, College of Computing and Information Technology, Shaqra University, Shaqra 11961, Saudi Arabia.ORCID 0000-0001-9261-6133
Amnah AlshahraniDepartment of Computer Science, Applied College, Princess Nourah bint Abdulrahman University, Riyadh 11671, Saudi Arabia.ORCID 0000-0002-2239-9142
Mohamed Esmail KararDepartment of Industrial Electronics and Control Engineering, Faculty of Electronic Engineering (FEE), Menoufia University, Menouf 32952, Egypt.ORCID 0000-0002-0474-4723
Ebrahim A RamadanDepartment of Industrial Electronics and Control Engineering, Faculty of Electronic Engineering (FEE), Menoufia University, Menouf 32952, Egypt.

Funding

Princess Nourah bint Abdulrahman University PNURSP2024R732Shaqra University SU-ANN-2023015
6 · The paper itself

Abstract

Cardiac pacemakers are used for handling bradycardia, which is a cardiac rhythm of usually less than 60 beats per minute. Therapeutic dual-sensor pacemakers aim to preserve or restore the normal electromechanical activity of the cardiac muscle. In this article, a novel intelligent controller has been developed for implanted dual-sensor cardiac pacemakers. The developed controller is mainly based on intuitionistic fuzzy logic (IFL). The main advantage of the developed IFL controller is its ability to merge the qualitative expert knowledge of cardiologists in the proposed design of controlled pacemakers. Additionally, the implication of non-membership functions with the uncertainty term plays a key role in the developed fuzzy controller for improving the performance of a cardiac pacemaker over other fuzzy control schemes in previous studies. Moreover, the proposed pacemaker control system is efficient for managing all health-status conditions and constraints during the different daily activities of cardiac patients. Consequently, the healthcare of patients with implanted dual-sensor pacemakers can be efficiently improved intuitively.

Indexed as

cardiac diseasesdual-sensor pacemakersintelligent controlintuitionistic fuzzy logic

Identifiers

PMID39061773
PMCPMC11274039

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.